Credit score forecasting system using machine learning techniques e.g. convolutional neural networks, has random forest model for making predictions about future credit scores based on data using historical financial data
	LAKKSHAN K; REDDY M V S R; KARTHIK K; REVANTH K; SETTY K L N; ETHIRAJULU V
	2023-10-16
专利权人	BHARATH HIGHER EDUCATION & RES INST (BHAR-Non-standard)
申请日期	2023-10-16
专利号	IN202341069782-A
成果简介	NOVELTY - The system has a random forest model for training historical financial data and analyzes large amounts of data e.g. transaction history, credit utilization, payment history and financial data. The random forest model uses the data to make predictions about future credit scores based on data. USE - Credit score forecasting system using machine learning (ML) techniques e.g. convolutional neural networks (CNNs). Can also be used in fields e.g. finance, image processing, natural language processing and time-series forecasting. ADVANTAGE - The system helps lenders and financial institutions make informed decisions to extend credit to individuals or businesses, improves accuracy, provides highly accurate credit score predictions and clear insights into the factors which influence the credit score prediction, handles large datasets with multiple features, missing data and noisy data and outliers effectively, identifies non-linear relationships, is transparent, highly efficient, robust and resistant to overfitting, reduces the number of features and allows lenders to understand the reasons behind a particular credit score.
IPC 分类号	G06K-009/62 ; G06N-003/00 ; G06N-005/00 ; G06Q-040/02 ; G06Q-050/16
国家	印度
专业领域	信息技术
语种	英语
成果类型	专利
文献类型	科技成果
条目标识符	http://119.78.100.226:8889/handle/3KE4DYBR/19782
专题	中国科学院新疆生态与地理研究所
作者单位	BHARATH HIGHER EDUCATION & RES INST (BHAR-Non-standard)
推荐引用方式 GB/T 7714	LAKKSHAN K,REDDY M V S R,KARTHIK K,et al. Credit score forecasting system using machine learning techniques e.g. convolutional neural networks, has random forest model for making predictions about future credit scores based on data using historical financial data. IN202341069782-A[P]. 2023.

条目包含的文件
条目无相关文件。

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。